Total 53,723 skills, Data Processing has 2765 skills
Showing 12 of 2765 skills
Write SQL, TypeScript, and dynamic table transforms for Goldsky Turbo pipelines. Use this skill for: decoding EVM event logs with _gs_log_decode (requires ABI) or transaction inputs with _gs_tx_decode, filtering and casting blockchain data in SQL, combining multiple decoded event types into one table with UNION ALL, writing TypeScript/WASM transforms using the invoke(data) function signature, setting up dynamic lookup tables to filter transfers by a wallet list you update at runtime (dynamic_table_check), chaining SQL and TypeScript steps together, or debugging null values in decoded fields. For full pipeline YAML structure, use /turbo-pipelines instead. For building an entire pipeline end-to-end, use /turbo-builder instead.
通过ASIN获取亚马逊商品详细信息，包括标题、图片、五点描述、规格参数、A+页面、价格、评分评论、变体等。当用户提到亚马逊商品详情、ASIN查询、商品页面数据、Listing分析、五点描述提取、商品图片获取、变体查看、竞品Listing研究、价格查询、评论拆解、商品规格查询、Amazon product details, ASIN lookup, listing analysis, bullet points, variant info, product pricing, ratings and reviews, A+ content, product specifications, product images时触发此技能。即使用户未明确说"商品详情"，只要其需求涉及通过ASIN获取亚马逊商品页面的结构化数据，也应触发此技能。
Macro-economic and cross-asset analysis for crypto market context. Use this skill whenever the user asks about the broader economic environment and its effect on crypto or risk assets. Triggers include: macro outlook, interest rates, Fed policy, rate cut, rate hike, FOMC, yield curve, inverted yield curve, recession risk, inflation, CPI, PCE, jobs data, unemployment, GDP, 10-year yield, 2-year yield, spread, dollar strength, DXY, risk-on, risk-off, gold correlation, BTC vs S&P, cross-asset correlation, global markets, tech earnings impact on crypto, forex rates, euro, yen, China market, A-shares, economic calendar, macro environment.
Stereonet plots for structural geology using matplotlib. Create lower-hemisphere stereographic projections for orientation data. Use when Claude needs to: (1) Create stereonet plots for structural data, (2) Plot planes as great circles or poles, (3) Plot lineations with trend/plunge, (4) Generate density contours for orientations, (5) Calculate mean orientations and statistics, (6) Analyze fold axes with pi-diagrams, (7) Convert between strike/dip and trend/plunge formats.
Read data from two tabs in a Google Sheet to compare and identify differences.
Use to interpret qualitative feedback, trends, and risks across community channels.
Generate reproducible analysis artifacts — SQL queries, Python visualizations, and summary tables — as you work through a BigQuery data analysis. Use when asked to conduct a deep dive, exploratory analysis, or investigation that goes beyond a simple data lookup.
OpenDuck — open-source distributed DuckDB with differential storage, hybrid dual execution, and transparent remote database attach
Process data with custom algorithms
Forecast Generator - Auto-activating skill for Data Analytics. Triggers on: forecast generator, forecast generator Part of the Data Analytics skill category.
Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery: SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.
Create effective data visualizations with Python (matplotlib, seaborn, plotly). Use when building charts, choosing the right chart type for a dataset, creating publication-quality figures, or applying design principles like accessibility and color theory.